Prototype for Ear-Worn Sleep Bruxism Monitor
Budget: $250 – $750 USD
Hello,
We are currently developing an ear-worn wearable device designed to detect bruxism and jaw clenching during sleep, and we are looking to request prototype production.
The device is intended to include the following features:
1. EMG (Electromyography) Sensor – to monitor jaw muscle activity via the temporal muscle and give real-time biofeedback
2. MEMS Microphone – to detect grinding noise during sleep
3. SpO2, Heart Rate (HR), and Heart Rate Variability (HRV) Sensor – attached to the earlobe
4. Vibration Motor (LRA) – to provide real-time feedback to the user
5. BLE Communication – for data transmission to a mobile application
The main goal of the product is to monitor unconscious bruxism/clenching behaviors during sleep, provide feedback to users in real-time, and visualize the data through a connected app.
1. Sensor Configuration and Placement
• EMG (Electromyography) Sensor: Attached to the temporal muscle to measure muscle contraction, enabling the detection of bruxism or clenching activities and electric real-time biofeedback using same wire
• MEMS Microphone: Detects sound and works in conjunction with the EMG signal to differentiate between “muscle activity with sound” (bruxism) and “muscle activity without sound” (clenching).
• SpO2/HR/HRV Sensor (e.g., MAX30102): Attached to the earlobe to monitor oxygen saturation, heart rate, and heart rate variability (HRV). If HRV is abnormally high compared to baseline, the app alerts the user of a potentially increased risk of bruxism during sleep.
• Vibration Feedback Motor (LRA): Provides real-time haptic feedback when bruxism or clenching is detected, helping users become aware of and improve their unconscious habits.
• MCU (Seeed XIAO nRF52840): A compact microcontroller with built-in Bluetooth Low Energy (BLE), used for integrating sensor data and transmitting it to the mobile app.
⸻
2. Detection and Judgment Algorithm
• EMG + Microphone:
• EMG activity with sound → Bruxism
• EMG activity without sound → Clenching
• HRV Analysis:
• Sudden or significant deviations in HRV values → Increased risk of bruxism, triggers an alert in the app.
⸻
3. User Feedback
• Vibration Feedback: Delivers subtle vibrations to notify users in real time when bruxism or clenching occurs during sleep or even during daytime clenching.
• Mobile App Integration: Visualizes collected data, allowing users to track their behavior patterns with weekly/monthly analytics and receive personalized improvement tips.
⸻
4. Power & Design
• Battery: Powered by a 3.7V 100mAh rechargeable LiPo battery, designed for compact and efficient use.
• Form Factor: Aims for a lightweight and comfortable ear-clip or earbud-style design that can be worn conveniently during sleep or daily activities.
Thank you very much, and we look forward to your response.
We are currently developing an ear-worn wearable device designed to detect bruxism and jaw clenching during sleep, and we are looking to request prototype production.
The device is intended to include the following features:
1. EMG (Electromyography) Sensor – to monitor jaw muscle activity via the temporal muscle and give real-time biofeedback
2. MEMS Microphone – to detect grinding noise during sleep
3. SpO2, Heart Rate (HR), and Heart Rate Variability (HRV) Sensor – attached to the earlobe
4. Vibration Motor (LRA) – to provide real-time feedback to the user
5. BLE Communication – for data transmission to a mobile application
The main goal of the product is to monitor unconscious bruxism/clenching behaviors during sleep, provide feedback to users in real-time, and visualize the data through a connected app.
1. Sensor Configuration and Placement
• EMG (Electromyography) Sensor: Attached to the temporal muscle to measure muscle contraction, enabling the detection of bruxism or clenching activities and electric real-time biofeedback using same wire
• MEMS Microphone: Detects sound and works in conjunction with the EMG signal to differentiate between “muscle activity with sound” (bruxism) and “muscle activity without sound” (clenching).
• SpO2/HR/HRV Sensor (e.g., MAX30102): Attached to the earlobe to monitor oxygen saturation, heart rate, and heart rate variability (HRV). If HRV is abnormally high compared to baseline, the app alerts the user of a potentially increased risk of bruxism during sleep.
• Vibration Feedback Motor (LRA): Provides real-time haptic feedback when bruxism or clenching is detected, helping users become aware of and improve their unconscious habits.
• MCU (Seeed XIAO nRF52840): A compact microcontroller with built-in Bluetooth Low Energy (BLE), used for integrating sensor data and transmitting it to the mobile app.
⸻
2. Detection and Judgment Algorithm
• EMG + Microphone:
• EMG activity with sound → Bruxism
• EMG activity without sound → Clenching
• HRV Analysis:
• Sudden or significant deviations in HRV values → Increased risk of bruxism, triggers an alert in the app.
⸻
3. User Feedback
• Vibration Feedback: Delivers subtle vibrations to notify users in real time when bruxism or clenching occurs during sleep or even during daytime clenching.
• Mobile App Integration: Visualizes collected data, allowing users to track their behavior patterns with weekly/monthly analytics and receive personalized improvement tips.
⸻
4. Power & Design
• Battery: Powered by a 3.7V 100mAh rechargeable LiPo battery, designed for compact and efficient use.
• Form Factor: Aims for a lightweight and comfortable ear-clip or earbud-style design that can be worn conveniently during sleep or daily activities.
Thank you very much, and we look forward to your response.